This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2220
Wer: 0.1269

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6557	1.0	1453	0.2339	0.1604
0.1267	2.0	2906	0.2057	0.1422
0.1008	3.0	4359	0.1963	0.1356
0.0846	4.0	5812	0.2037	0.1308
0.0727	5.0	7265	0.2029	0.1299
0.0639	6.0	8718	0.2064	0.1301
0.0559	7.0	10171	0.2061	0.1273
0.0493	8.0	11624	0.2108	0.1278
0.0437	9.0	13077	0.2183	0.1273
0.0398	10.0	14530	0.2220	0.1269

Framework versions

Transformers 4.48.0
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1

aman-batazia/wav2vec-commonvoice-2

wav2vec-commonvoice-2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

aman-batazia/
wav2vec-commonvoice-2